Integrations
Summary: collibra_data_citizens outlines best practices for integrating with Collibra, emphasizing out-of-the-box features to optimize integration processes. Key strategies include prioritizing native/direct integration and evaluating JDBC connectors. Custom integrations using languages such as Java or Python utilize REST APIs for broader functionalities. Integration selection is guided by various factors including installation time and Collibra support features. However, Damien R notes that the "Integration selection key factors" table appears to be broken.
Applies to: integrating with Collibra.
Collibra offers a wide range of ways to connect to external data sources. Follow the recommendations and key component overview in this article to optimize your Collibra Data Intelligence Platform metadata connector or integration approach.
Impact
Reduce time and resource costs for integration delivery, installation and support.
Leverage Collibra out-of-the-box features.
Background - integration types overview
Native/Direct integrations are available in Collibra as out-of-the-box features, such as S3 and Tableau.
Metadata connectors are mostly available in
Collibra Marketplace
or on the technology vendor website:
JDBC connectors certified by Collibra.
Vendor supported JDBC connectors non-certified by Collibra.
Spring Boot applications installed as a standalone integration app from Collibra Marketplace.
Data Lineage
is available as a standalone application:
Technical Lineage Harvester as a standalone JAVA application. We support three types:
Data Source as JDBC.
Data Source as ETL.
BI Harvesters such as PowerBI, Tableau and MicroStrategy.
Custom integration usually developed on any ESB (Enterprise Service Bus) or using object-oriented language, for example Java Spring Boot service or Python service:
Custom Integrations using Java or Python can fully utilize REST IMPORT APIs to implement non-supported integrations.
We can extend use cases and use Collibra workflows in these integrations which can be called by custom integrations using REST API for bidirectional integrations and workflow task assignments to specific roles inside Collibra.
Insights Data Access which provide APIs can be used to extract data from Collibra. This helps in giving an overview of Collibra Maturity Assessments.
Manual data import as Excel files and .csv files from Collibra UI.
Collibra Data Quality & Observability Connectors used to extract the DQ Rules from Collibra DQ into Collibra Data Intelligence Platform. This is currently only supported in Edge.
Best practice recommendations
Integration type selection and key decision factors
This section aims to help you chose the best integration method to minimize your resource time and cost, and leverage the out-of-the-box feature set for your unique use case.
We recommend that you evaluate the different integration options in the following order of priority. Stop at the first one that provides the functionality you require:
Priority
Integration approach
1
Native/Direct integration.
2
JDBC connectors certified by Collibra.
3
Vendor supported JDBC connectors non-certified by Collibra.
4
Spring Boot applications installed as a standalone integration app from the Collibra Marketplace.
5
Custom integration developed by any ESB or custom integration service.
Integration selection key factors
Below is a table of integration type and decision-making factors you should consider when choosing a new integration method:
Collibra Supported
Time to install and configure
Jobserver or Edge required
Upgrade process
License vendor
Collibra features enabled
Collibra native integration
Yes
Low
S3 integration: Edge or Jobserver required.
Automatic, during DGC releases timeline.
Collibra
Jobserver metadata connectors
Supporting party has to be checked on Collibra Marketplace.
Low
Jobserver
Manual update once new version released.
Metadata connector provider (might not be supported when Free of charge)
Profiling, Data Sampling, Classification
Edge capability templates
Yes
Low
Edge
Automatic, during Collibra releases timeline.
Collibra
Profiling, Data Sampling , Classification
Collibra Data Quality & Observability connector
Yes
Low
Edge
Automatic, during Edge release.
Collibra
Spring Boot applications
Supporting party has to be checked on Collibra Marketplace.
Medium
Not needed
Manual
Metadata connector provider
Data Lineage
Yes
Medium
Not needed
Manual
Collibra
Technical Lineage, Business Lineage
Reporting Insights
Yes
Medium
Not needed
Manual
Collibra
Reporting insights
Custom integration as any EBS or custom integration service
No
High
Not needed
Depending on ESB Platform or Custom Integration Technology
ESB Platform Vendor or Technology Vendor
Custom integration as any EBS or custom integration service
Validation Criteria
One of the important validation criteria is “Time to Install and Configure”, where values are:
Low is < 1 day
Medium is 1 - 5 days (usually 1-2 days)
High is 5 - 20 or more days (usually 10+ days).
Please refer to the above section for details about time needed.
Additional Information
For more information see the following resources:
See the Collibra documentation Center for more information on any of the above elements.
Many integrations and connectors are available on the Collibra Marketplace.
Damien R
·1 year ago@collibra_data_citizens It seems like the "Integration selection key factors" table is broken